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Healthcare Spent $1.4 Billion on AI Last Year. At IPX, Almost Nobody Talked About It.
I just got back from IPX Congress in New York. Two days. Patient experience leaders from across the country. Panels on small gestures, service recovery, staff burnout, leadership rounding, the human side of care delivery.
Here is the thing nobody at home would have predicted.
In two full days of programming, almost nobody talked about AI.
There was a passing mention here and there. Someone made a joke about Epic owning everything. One speaker asked the room how many had typed their facility name into ChatGPT to see what showed up. That was about it.
Now consider what the broader industry did during the same window. According to my own research before the conference, healthcare spent $1.4 billion on healthcare-specific generative AI in 2025. That is roughly three times what the industry spent in 2024. Seven out of ten providers report having an AI strategy in place or in development. By 2030, projections suggest 20 to 30 percent of all U.S. healthcare interactions will be shaped or guided by AI in some form.
And yet patient trust in physicians and hospitals has dropped from 71.5 percent to 40 percent over the last several years. Complaints against hospitals are up 79 percent over five years. Only 44 percent of Americans rate U.S. healthcare quality as good. The trust line is moving in the opposite direction of the technology line.
Two days in a room with the people who actually run patient experience for the biggest systems in the country, and the dominant industry conversation was almost completely absent.
That was the story for me.
Why the Best CXOs Are Not Leading With AI
The Chief Experience Officers I spent two days with are not anti-technology. Most of them are running AI initiatives in their organizations right now. They are not talking about AI on stage because they already learned the lesson the rest of the industry is still paying tuition on.
Strategy first. Technology second.
If you put technology in front of strategy, what you get is a faster version of a broken process. A faster broken process is not patient experience. It is operational decoration.
That is why the IPX stage was full of practices like leadership rounding, commit-to-sit, the LAST model for service recovery, and one proactive post-discharge call. These are not technology problems. They are standards problems. The CXOs who have been doing this for 20 years know that the trust line moves when the standards move, regardless of what software the organization buys next.
Here is the part most healthcare AI vendors do not want you to read.
A contact center that cannot tell you why patients are calling, what gets resolved on the first interaction, and which patients are quietly disengaging will not be fixed by adding a chatbot. It will be made faster at confusing patients. The metrics may even look better for a quarter. The retention will not.
That is where most of the $1.4 billion is going. Into systems that were never built for trust, hoping the AI layer will compensate for it.
It does not compensate for it. It accelerates it.
What I Said on Stage
This was the heart of my own talk at IPX.
I told the room the same thing I am telling you. The technology is doing exactly what it was built or bought to do. It is just not necessarily what patients need. The disconnect is not in the AI. The disconnect is in the operational model the AI is being asked to run on top of.
The Trust Algorithm is the frame I shared on stage. You already know the five signals: Accessibility, Resolution, Continuity, Proactivity, Recovery. The question I put to the room was not whether those signals matter. The question was whether the technology you are buying serves them.
When I run the Trust Algorithm at an organization, I am not asking whether the technology is good. I am asking whether the operational model the technology runs on top of is built for trust in the first place. Most are not. That is the strategy gap.
If you fix the strategy first, AI accelerates trust. If you do not, AI accelerates the absence of it.
The IPX Speakers Were Saying This Without Saying It
Read the practices I shared in last week's deliverable, or any summary of an IPX panel, and you will see the same pattern.
Rick Evans at NewYork-Presbyterian talked about earbuds out when staff enter the building. That is a Continuity practice. The patient feels known when the people walking past them are paying attention.
Alisha Bronne at North Central Bronx Hospital talked about commit to sit. That is a Continuity practice with an Accessibility surface. Eye-level interactions change the patient's read of presence.
Quimberly de Leon at The Mount Sinai Hospital walked through the LAST model for service recovery. Listen, Acknowledge, Solve, Thank. That is a Recovery practice. Failures become loyalty when the response feels designed instead of improvised.
Thomas Tull at Ballad Health talked about making it easy. Every entry point, every touchpoint, every channel reduced to the simplest path the patient can follow. That is an Accessibility practice that works because the entire team understands the standard.
Wren Lester said it most directly. If patient experience is not on your formal strategic plan as a pillar, with specific metrics, you have to make that appointment with your senior leader and ask for it.
That is the meta-practice. Get the patient voice on the strategy before you put it on the technology. Otherwise you are buying tools to scale a model that was never designed to produce trust.
What This Looks Like at My Old Organization
A short story from earlier in my career.
I was running parts of the member experience operation for a multi-regional payvider. The team I inherited had been measuring everything by call duration and after-call work. The numbers looked fine. The members did not feel that way.
We rebuilt around something different. A structured touchpoint process that defined what every member interaction was supposed to accomplish, in what order, with what context carrying forward to the next one. First-call resolution. Whether the next interaction reflected what the system already knew about the member. Whether the third interaction felt like progress instead of repetition.
The result: we retained members at over a 90% retention rate.
Compliance metrics did not get worse. They got better. Performance metrics did not get worse. They got better. They were not in conflict. They were the same thing, when the system was designed correctly.
That is the lesson I carry into every conversation now, especially with leaders who do not have a dedicated PX team.
You do not need scale to design well. You need a small number of standards, written down, that everybody knows. The first interaction has to count. The second has to remember the first. The third has to feel like progress, not repetition.
That is operationally simple. It is culturally hard.
It is also exactly the foundation that makes AI worth deploying. Without it, AI is a faster version of confusion. With it, AI compounds a model that already produces trust.
What This Means for You
The hardest part of patient experience work, especially for leaders without a dedicated PX team, is not the doing. It is the proving.
The CFO wants to know what patient experience is worth in dollars. The board wants to see retention numbers. The COO wants to know whether the contact center investment is producing measurable returns. And patient experience, as it is typically measured, struggles to answer those questions in the language those rooms speak.
That is the gap I keep running into. Not whether leaders care about patient experience. Whether they can tie it to revenue with enough specificity to defend the budget for it.
That is what the Trust Algorithm is built to answer. Not just where trust is breaking, but what each gap is costing you in revenue, retention, and operating margin.
If you want to start putting numbers to the trust gaps in your own organization, the Trust ROI Calculator is the first place to look. It takes a few inputs you already have (revenue base, current retention rate, complaint volume, contact center metrics) and gives you back a dollar figure on the trust gaps that are quietly costing you today. It is the same tool I use in early conversations with health system leaders to anchor the COMO calculation in their own numbers.
It will not tell you what to buy. It will tell you what each unaddressed gap is costing you, in your own revenue terms. That is the language that gets PX on the strategic agenda, with or without a dedicated PX team.
When You Are Ready for the Next Step
The ROI Calculator gives you the headline number. The Trust Algorithm Diagnostic gives you the operational map underneath it. It is a full five-signal audit, including the assessment, operational data review, mystery shopping, and financial modeling, designed for organizations that need to know exactly where trust is breaking and how much each gap is costing them. It produces findings, not opinions.
From the diagnostic, the Trust Blueprint translates the findings into a prioritized action plan. Workflow redesign, vendor criteria, pilot design, KPI dashboard. The Blueprint is what makes the diagnostic actionable.
Some organizations also bring me on as a fractional CXO. I become the person carrying the patient voice into your strategy meetings, your vendor selection conversations, your EHR rollout, your hiring plan. The role exists for as long as you need it. When you are ready to hire someone permanent, I help you scope the role and the metrics they will be accountable for.
One Last Thing
Reply with the trust signal you think your organization is leaking the most today. I read every reply. I am building a running pattern map of what is breaking for organizations growing into PX, and your read on your own operation is the most useful data I get.
Until next Wednesday,
Ebony
Ebony sitting at table talking on phone
Ebony Langston is the founder of The Patient Experience Strategist™ and a fractional Chief Experience Officer for healthcare organizations rebuilding patient trust as a margin strategy. She has 20+ years of operations experience inside Fortune 100 healthcare organizations and writes weekly for the C-suite executives and PX leaders working to translate patient experience from a cost line into a revenue engine.
